Public infrastructure settings these days are feared to be more and more vulnerable to security threats. The world has suffered much loss of life and property due to terrorist incidents. In order to protect human lives, public infrastructure facilities such as rail and road transport and shopping malls from potential security threats, it has become imperative to build surveillance systems that can monitor a scene and automatically detect and report suspicious events. The importance of surveillance systems is evident from the increasing number of closed circuit television (CCTV) cameras we see in in train stations, airports, shopping malls, traffic junctions and streets our day-to-day life. For instance, it has been reported that United Kingdom has one of the largest camera network with over 4.2 m cameras this is approximately 1 for every 14 people.
Much of the content recorded from surveillance scenes are rarely screened and merely serve as record for forensic analysis. Moreover, searching for a specific occurrence in this enormous quantity of data amounts to looking for a needle in a haystack. A surveillance camera becomes more usable if it is packaged with intelligence to detect and report events in close to real time.
Video based surveillance systems are widely used to monitor sensitive areas for dangerous behavior, unusual activities and intrusion detection. This process generally involves humans monitoring a continuous stream of video from single or multiple sources looking to find such abnormal behavior. This process is highly inefficient given the rarity of occurrence of such abnormal events. Most attempts at automating this system require a set of predefined rules describing what sort of events are to be considered abnormal. Such rule based systems describe abnormal events using rules such as ‘detect people crossing a virtual line’; ‘detect any activity within a bounded region’; ‘detect vehicles stopping in a region for a longtime’; etc. Defining rules specific to a scene requires a human to analyze the scene being monitored and create these rules. In addition to this, it is very difficult to create rules to describe most abnormal behavior like ‘fight in a crowd’ and ‘a person loitering in a region with standard people movement’.